We draw on the life course framework to validate hypotheses regarding the role of the neighborhood environment in the transmission of Type 2 Diabetes (T2DM) risk from parents to offspring. The research will transform our understanding of how neighborhood features, and the interplay between neighborhood and family characteristics, affect T2DM risk over the life course. The intergenerational transmission of T2DM to offspring has long been demonstrated. Our past research has shown that greater neighborhood walkability is associated with lower risk of obesity, and it suggests that the activity environment may have an important impact on moderating or exacerbating T2DM risk as well. For this study, we expand the scope of neighborhood features to include food environments. We propose to estimate the risk of T2DM as a function of both familialT2DM histories and neighborhood environments. We draw on comprehensive, longitudinal records in theUtah Population Database, which contain individual-level data on medical, residential, and familial variables spanning decades for an entire population. These intergenerational data will be integrated with measures of neighborhood characteristics across time to construct longitudinal family health and neighborhood histories, which we will use, following a life course approach, to characterize T2DM risk. Using innovative methods, we capitalize on small-area measures of the built environment to consider the roles of familial and neighborhood factors that may independently and interactively influence T2DM risk. The proposed analyses will address the following questions: ? How can longitudinal, geo-referenced databases and maps depict dynamic spatial characteristics of critical sociodemographic and physical neighborhood-level risk factors for T2DM? ? What are the ways in which neighborhood component trajectories modify how familial histories of T2DM are associated with the risk of T2DM among offspring? ? What are the potential quality-of-life improvements and economic benefits associated with altering modifiable neighborhood features linked to T2DM risk? This study will make several innovative contributions to the diabetes literature. First, to account for the long latency period for the onset of T2DM, we will use decades of data to operationalize neighborhood risk in terms of walkability and food environments (under consideration of neighborhood changes over time and migration between neighborhoods). Second, we will utilize existing genealogical records and objective family health histories, a feature not found in prior T2DM studies, to assemble a cohort of parents and offspring in four urban Utah counties, differentiating between Hispanic and non-Hispanic white populations. Third, the combination of intergenerational and neighborhood data allows for a multi- level study of T2DM risk to inform prevention policies. Fourth, we estimate the costs of diabetes attributable to neighborhood conditions subject to policy changes.